You want to study what factors predict someone's approval of the government. You decide to use presidential approval ratings as a means of measuring a person's approval of government. As a proof of concept (a pilot study), you ask a group of friends about their approval of President Biden and President Trump. You first ask several friends what political party they affiliate with and found that 10 identify as democrat, 12 as republican and 8 as independent. You ask half of these friends (at random) what their approval rating of President Biden and then ask the other half what is their approval rating of Trump. Approval rating is rated on a scale from 0-10, 0 meaning no approval at all and 10 being highest approval. You run a 2x3 factorial ANOVA for this pilot study, the following table is the dataset for your pilot study:

President	Political Affiliation	T row =
Democrat	Republican	Independent
Trump	1 2 1 3 0 M = 1.4 T = 7 SS = 5.2	6 5 7 10 9 4 M = 6.83 T = 41 SS = 26.83	3 6 5 4 M = 4.25 T = 18 SS = 5	66
Biden	8 6 7 9 6 M = 7.2 T = 36 SS = 6.8	3 2 4 1 0 2 M = 2 T = 12 SS = 10	5 3 6 6 M = 5 T = 20 SS = 6	68
T column =	43	53	38	N = 30 G = 134 Summation of x squared = 814

1. State the null and alternative hypotheses for the main effects and the interaction.

1. Fill out the rest of the ANOVA table below using the information in the table above:

Source	SS	df	MS	F
Between			--	--
Factor A (President)	1.74			F( , ) =
Factor B (Pol. Aff.)	0.95			F( , ) =
A x B	154.55			F( , ) =
Within				--
Total			--	--

1. Calculate the effect size (n squared) for each of the main effects and the interaction.

1. Use a F-ratio to p-value calculator (https://www.socscistatistics.com/pvalues/fdistribution.aspx) to find the p-value for each F ratio. What decision do you make in regards to the null hypothesis?

1. Given the information generated, report your findings as if writing in an APA formatted article. Include the results for the main effects and interaction, and what they mean in relation to the example pilot study.